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reverse_add_replicate_eval17_SGD_largelr

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Safetensors
nanogpt
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  1. README.md +219 -0
  2. config.json +18 -0
  3. generation_config.json +4 -0
  4. model.safetensors +3 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: reverse_add_replicate_eval17_SGD_largelr
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # reverse_add_replicate_eval17_SGD_largelr
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.0682
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+ - Accuracy: 0.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.01
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 128
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+ - optimizer: Use OptimizerNames.SGD and the args are:
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+ No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|
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+ | No log | 0 | 0 | 2.6767 | 0.0 |
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+ | 4.9353 | 0.0064 | 100 | 2.4615 | 0.0 |
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+ | 4.7709 | 0.0128 | 200 | 2.3942 | 0.0 |
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+ | 4.7347 | 0.0192 | 300 | 2.3708 | 0.0 |
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+ | 4.6969 | 0.0256 | 400 | 2.3638 | 0.0 |
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+ | 4.6897 | 0.032 | 500 | 2.3638 | 0.0 |
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+ | 4.6699 | 0.0384 | 600 | 2.3546 | 0.0 |
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+ | 4.6818 | 0.0448 | 700 | 2.3426 | 0.0 |
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+ | 4.6744 | 0.0512 | 800 | 2.3378 | 0.0 |
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+ | 4.6436 | 0.0576 | 900 | 2.3310 | 0.0 |
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+ | 4.6145 | 0.064 | 1000 | 2.3249 | 0.0 |
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+ | 4.5831 | 0.0704 | 1100 | 2.3182 | 0.0 |
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+ | 4.5523 | 0.0768 | 1200 | 2.3065 | 0.0 |
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+ | 4.5151 | 0.0832 | 1300 | 2.2944 | 0.0 |
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+ | 4.4616 | 0.0896 | 1400 | 2.2827 | 0.0 |
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+ | 4.4618 | 0.096 | 1500 | 2.2629 | 0.0 |
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+ | 4.3922 | 0.1024 | 1600 | 2.2538 | 0.0 |
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+ | 4.3751 | 0.1088 | 1700 | 2.2454 | 0.0 |
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+ | 4.3695 | 0.1152 | 1800 | 2.2374 | 0.0 |
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+ | 4.3369 | 0.1216 | 1900 | 2.2359 | 0.0 |
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+ | 4.3101 | 0.128 | 2000 | 2.2223 | 0.0 |
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+ | 4.3527 | 0.1344 | 2100 | 2.2710 | 0.0 |
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+ | 4.2841 | 0.1408 | 2200 | 2.2447 | 0.0 |
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+ | 4.2868 | 0.1472 | 2300 | 2.2472 | 0.0 |
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+ | 4.3244 | 0.1536 | 2400 | 2.2025 | 0.0 |
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+ | 4.2553 | 0.16 | 2500 | 2.2152 | 0.0 |
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+ | 4.2581 | 0.1664 | 2600 | 2.1993 | 0.0 |
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+ | 4.2062 | 0.1728 | 2700 | 2.1933 | 0.0 |
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+ | 4.2716 | 0.1792 | 2800 | 2.2023 | 0.0 |
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+ | 4.2505 | 0.1856 | 2900 | 2.2279 | 0.0 |
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+ | 4.1869 | 0.192 | 3000 | 2.1867 | 0.0 |
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+ | 4.2739 | 0.1984 | 3100 | 2.1963 | 0.0 |
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+ | 4.159 | 0.2048 | 3200 | 2.2119 | 0.0 |
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+ | 4.2733 | 0.2112 | 3300 | 2.2181 | 0.0 |
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+ | 4.1322 | 0.2176 | 3400 | 2.1933 | 0.0 |
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+ | 4.2175 | 0.224 | 3500 | 2.1887 | 0.0 |
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+ | 4.192 | 0.2304 | 3600 | 2.1744 | 0.0 |
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+ | 4.1938 | 0.2368 | 3700 | 2.1893 | 0.0 |
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+ | 4.1599 | 0.2432 | 3800 | 2.1772 | 0.0 |
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+ | 4.1543 | 0.2496 | 3900 | 2.1795 | 0.0 |
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+ | 4.1987 | 0.256 | 4000 | 2.1793 | 0.0 |
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+ | 4.1409 | 0.2624 | 4100 | 2.1693 | 0.0 |
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+ | 4.0957 | 0.2688 | 4200 | 2.1904 | 0.0 |
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+ | 4.1336 | 0.2752 | 4300 | 2.1607 | 0.0 |
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+ | 4.1676 | 0.2816 | 4400 | 2.1702 | 0.0 |
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+ | 4.1273 | 0.288 | 4500 | 2.1720 | 0.0 |
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+ | 4.0858 | 0.2944 | 4600 | 2.1565 | 0.0 |
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+ | 4.0708 | 0.3008 | 4700 | 2.1580 | 0.0 |
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+ | 4.0653 | 0.3072 | 4800 | 2.1831 | 0.0 |
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+ | 4.0605 | 0.3136 | 4900 | 2.1759 | 0.0 |
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+ | 4.1233 | 0.32 | 5000 | 2.1536 | 0.0 |
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+ | 4.1175 | 0.3264 | 5100 | 2.1749 | 0.0 |
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+ | 4.0947 | 0.3328 | 5200 | 2.1421 | 0.0 |
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+ | 4.0778 | 0.3392 | 5300 | 2.1630 | 0.0 |
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+ | 4.0713 | 0.3456 | 5400 | 2.1826 | 0.0 |
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+ | 4.1213 | 0.352 | 5500 | 2.1499 | 0.0 |
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+ | 4.0291 | 0.3712 | 5800 | 2.1461 | 0.0 |
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+ | 4.0493 | 0.3776 | 5900 | 2.1621 | 0.0 |
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+ | 4.0856 | 0.384 | 6000 | 2.1467 | 0.0 |
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+ | 4.0359 | 0.4096 | 6400 | 2.1355 | 0.0 |
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+ | 3.9999 | 0.6336 | 9900 | 2.1102 | 0.0 |
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+ | 3.9219 | 0.9088 | 14200 | 2.0706 | 0.0 |
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+ | 3.9017 | 0.9984 | 15600 | 2.0682 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.0
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+ - Pytorch 2.5.1
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.1
config.json ADDED
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+ {
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+ "architectures": [
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+ "NanoGPT"
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+ ],
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+ "bias": true,
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+ "block_size": 256,
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+ "dropout": 0.0,
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+ "model_type": "nanogpt",
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+ "n_embd": 384,
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+ "n_head": 6,
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+ "n_layer": 6,
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+ "nonlinearity": "RELU",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.46.0",
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+ "use_NoPE": true,
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+ "use_layernorm": true,
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+ "vocab_size": 14
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+ }
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "transformers_version": "4.46.0"
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+ }
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